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Genetics and Epigenetics

Information bias in measures of self-reported physical activity

International Journal of Obesity volume 42, pages 2062–2063 (2018)Cite this article

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In their recent genome-wide association study (GWAS) using UK Biobank, Klimentidis and colleagues [1] identified nine loci associated with self-reported physical activity (PA). We believe that rather than capturing genetic architecture of habitual PA, genetic variants identified in this GWAS, may at least in part reflect information bias in self-reported data, attributable to participants’ cognitive ability of reporting PA.

One of the strongest signals in this study was for APOE, with its risk allele being paradoxically associated with greater self-reported PA. Given the well-established association of APOE ε4 allele with Alzheimer’s disease [2], the direction of the association is unexpected. Although this could be attributed to selection bias as discussed by the authors (that is, APOE carriers in the study are enriched for healthy lifestyles), this association was not replicated using accelerometer-based PA. Although accelerometer data is only available for a subsample, the loss of power would be compensated by an even stronger selection bias operating in this subsample and objectively-assessed measures being less ‘noisy’. We believe that the more plausible explanation for this paradoxical association is that participants with lower cognitive function in the study tend to over-report their activity levels. This becomes more apparent in the genetic correlation analyses (which aggregate SNP effects across the genome), where increases in self-reported PA were found to be correlated with decreased intelligence, years of schooling, and lower childhood IQ, but increased risk for various mental-health related traits, including schizophrenia, PGC cross-disorder, Bipolar disorder, and Alzheimer’s disease. In contrast, none of these correlations surfaced in the analyses based on accelerometer-based PA, presumably as the objectively-assessed measures were not subject to the bias caused by participants’ cognitive ability of reporting PA.

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References

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  1. Australian Center for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia

    Stephanie Folley, Ang Zhou & Elina Hyppönen

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  1. Stephanie Folley
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  2. Ang Zhou
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  3. Elina Hyppönen
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Correspondence to Elina Hyppönen.

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Folley, S., Zhou, A. & Hyppönen, E. Information bias in measures of self-reported physical activity. Int J Obes 42, 2062–2063 (2018). https://doi.org/10.1038/s41366-018-0223-x

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